ℍ𝕆𝕎 ℙℝ𝕆𝔻𝕌ℂ𝕋 𝔻𝔸𝕋𝔸 𝕄𝔸ℕ𝔸𝔾𝔼𝕄𝔼ℕ𝕋 ℙ𝕃𝔸𝕐𝕊 𝕍𝕀𝕋𝔸𝕃 ℝ𝕆𝕃𝔼 𝕀ℕ 𝔽𝔸𝕊ℍ𝕀𝕆ℕ 𝕀ℕ𝔻𝕌𝕊𝕋ℝ𝕐

While the design process we learned in school provides a foundation, the industry takes it a step further. Inspirations, mood boards, and design essence may align, but industry design is significantly data-backed. In fashion, predicting product sales is integral during design, shifting focus from pure imagination to customer needs and market demands. Design, now more than ever, is a harmonious blend of creativity and strategic data analysis. 💡📊

McKinsey & Company delivers an in-depth report, outlining effective strategies for leveraging data analytics to enhance every facet of fashion business. 

𝕯𝖆𝖙𝖆 𝕮𝖍𝖆𝖑𝖑𝖊𝖓𝖌𝖊𝖘 𝖎𝖓 𝕱𝖆𝖘𝖍𝖎𝖔𝖓 & 𝕷𝖚𝖝𝖚𝖗𝖞:

The absence of high-quality data, clean taxonomies, and a common understanding of data cripples analytics journeys, especially concerning core data sets like POS transactions and SKU–product data.

𝕾𝖙𝖗𝖆𝖙𝖊𝖌𝖎𝖈 𝕯𝖆𝖙𝖆 𝕺𝖕𝖊𝖗𝖆𝖙𝖎𝖓𝖌 𝕸𝖔𝖉𝖊𝖑

Successful fashion companies adopt a value-backed data-operating-model framework across various domains, establishing clear ownership for each business unit to define, monitor, and ensure uniform data quality, leading to a 50% improvement in compliance with data-quality rules.

𝕸𝖆𝖈𝖍𝖎𝖓𝖊 𝕷𝖊𝖆𝖗𝖓𝖎𝖓𝖌 𝖋𝖔𝖗 𝕰𝖓𝖍𝖆𝖓𝖈𝖊𝖉 𝕼𝖚𝖆𝖑𝖎𝖙𝖞:

Leveraging machine-learning algorithms, particularly in customer information, proves to be a sophisticated solution, as seen in the fashion industry, where pattern-recognition algorithms eliminate duplicates, showcasing a powerful tool for enhancing data quality and personalizing customer e-commerce experiences, resulting in a remarkable growth of digital sales by 30 to 50%.

Link for the McKinsey full report: https://www.mckinsey.com/industries/retail/our-insights/jumpstarting-value-creation-with-data-and-analytics-in-fashion-and-luxury

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